Lab 2 — Score Role Exposure and Build a Skills Adjacency Map

COMPEL Specialization — AITE-WCT: AI Workforce Transformation Expert Lab 2 of 5

Lab objective

Apply the task-level decomposition and classification method (Article 24) to three described roles, score exposure and augmentation potential, and build a skills-adjacency map (Article 5) that identifies realistic redeployment candidates for employees whose current roles face substantial exposure.

Prerequisites

• Completion of Articles 4 (role exposure scoring), 5 (skills adjacency), and 24 (task-level decomposition) of this credential.
• Familiarity with Template 2 (Role Exposure and Skills-Adjacency Assessment Workbook).

The three roles

Role A — Commercial Underwriter (mid-tier European bank)

The commercial underwriter reviews mid-market company loan applications, drafts underwriting memos, makes credit recommendations, and presents to credit committee. A typical week: 30 applications reviewed; 15 memos drafted; 5 presentations; 8 client calls; 4 hours of training and professional development; 6 hours of collaboration and peer review. Tenure: average 8 years in role; common prior roles include credit analyst and portfolio analyst. Current AI touchpoints: a draft-generation assistant produces initial memo drafts from application data; the underwriter reviews and edits; current adoption in pilot at 30% of applications.

Role B — Retail Contact Centre Agent (same bank)

The contact centre agent handles inbound customer calls on retail banking matters: account queries, card issues, online banking support, general information, complaint intake. A typical shift: 60 calls, 18 messages, 2 hours of training. Tenure: average 3 years in role; common prior roles include retail branch teller and customer-service in other industries. Current AI touchpoints: a knowledge-base retrieval assistant surfaces relevant policy content during calls; an auto-notes feature drafts the call log; a chatbot handles simpler query triage before calls reach the agent.

Role C — Credit Risk Analyst (same bank, risk function)

The credit risk analyst builds and maintains credit-risk models for retail and commercial portfolios, produces risk reports for the risk committee, and supports underwriting and portfolio-management decisions. A typical week: 20 hours of model work, 8 hours of analysis on specific cases, 6 hours of report drafting, 4 hours of stakeholder meetings, 4 hours of training and research. Tenure: average 6 years; common prior roles include quantitative analyst in other banks. Current AI touchpoints: the analyst uses statistical programming tools daily; machine-learning model development is part of the role; a research-assistant AI is in pilot for literature review and code-snippet generation.

Step-by-step method

Step 1 — Task elicitation (25 minutes per role, 75 minutes total)

For each role, produce a task inventory of 15–25 tasks. Use the descriptions above plus plausible extension — incumbents at each of these roles spend time on specific tasks not enumerated in the description. Apply the coordination-work correction from Article 24: include at least three tasks that represent coordination, synthesis, or knowledge-work activity.

For each task, record:

• Task name.
• Approximate time per week.
• Brief description (1 sentence).

Step 2 — Task classification (25 minutes per role, 75 minutes total)

For each task, score on three dimensions per Article 24:

• AI exposure (0–3). 0 = no current AI capability; 1 = AI does portions with adjustment; 2 = AI does most with light review; 3 = AI does end-to-end with exception handling.
• Augmentation value (low/medium/high). Depends on frequency, quality sensitivity, organisational value.
• Human-centricity (low/medium/high). Depends on judgment, relational content, professional accountability, contextual work.

Use the classification cells of Template 2 (Role Exposure and Skills-Adjacency Assessment Workbook).

Step 3 — Role-level aggregation (15 minutes per role, 45 minutes total)

For each role, produce the aggregation from Article 24:

• Exposure profile: fraction of time at each exposure level.
• Augmentation-value distribution: where is the augmentation value concentrated.
• Human-centricity concentration: identify the irreducibly-human core.
• Total task time versus role working hours: does the task inventory account for the whole role.

Step 4 — Skills-adjacency mapping (30 minutes)

Using the ESCO European skills taxonomy (or the Lightcast open subset as an alternative) as the skills reference, map the skills implicit in each of the three roles. Then identify, for each role:

• Three skills-adjacent roles within the bank to which the incumbent’s skills are transferable with modest additional development (less than 6 months).
• Three skills-adjacent roles requiring moderate additional development (6–18 months).
• Three skills-adjacent roles requiring substantial additional development (beyond 18 months).

Consider roles such as portfolio analyst, risk analyst, product manager, branch manager, compliance officer, wealth adviser, treasury analyst, data analyst, customer-experience analyst, operations analyst. Justify each mapping with reference to the specific skills that transfer and the skills that must be developed.

Step 5 — Redeployment recommendation (15 minutes)

For each of the three roles, recommend:

• Whether the role, as currently constituted, should be retained, redesigned, or retired in the programme’s first year.
• For incumbents whose role is redesigned or retired: which of the skills-adjacent roles are the strongest redeployment candidates.
• What specific development pathway the redeployment would require.

The recommendation is the deliverable’s executive section — what you would present to the coalition for decision.

Deliverable

A completed role-exposure workbook (Template 2) populated for all three roles, with:

• Task inventory, classification, and role-level aggregation for each role.
• Skills-adjacency map linking each role to three adjacent roles at each development tier (short / moderate / substantial).
• Redeployment recommendation section.

Total artefact length: 8–15 pages (workbook format).

Scoring rubric

Passing standard: 75 points.

Worked example — partial reference

For Role A (Commercial Underwriter), a partial reference task classification:

Role-level aggregation: the drafting work is highly exposed; the judgment, relational, and coordination work is largely unexposed. The role redesigns toward review, dialogue, and professional judgment, with the drafting work shifted substantially to AI. The redesigned role is commercially viable; redeployment is not the primary pathway for the current incumbent population.

Expected depth: similar specificity across all tasks and all three roles.

Lab discussion questions

• Which role was hardest to decompose well? Why?
• Where did the coordination-work correction most materially change the classification?
• For which role was skills-adjacency most constrained (fewest realistic redeployment targets)? What are the implications for the programme?
• How would your redeployment recommendations change if the bank’s labour-market conditions were more or less tight than the current state?

Connection to other labs

The output of this lab feeds Lab 3 (literacy curriculum design — the roles here inform the role-to-level mapping) and Lab 5 (role redesign — the commercial underwriter role returns there for full redesign).

Quality rubric — self-assessment of lab